1. Field of Invention
The present invention relates to a method for identifying hand-written style, and more particularly to an on-line identifying method of hand-written Arabic letter.
2. Description of Related Arts
Arabic, as the language of Mohammedanism and <<Alcoran>>, is one of the primary languages of the world and is widely used in the world. Arabic letter is a written form of Arabic. At present, the research on identifying the Arabic letter has become one of the important researches.
An identifying method of printed Arabic letter based on boundary characteristic is disclosed in a Chinese patent application CN 101038627 an identifying method of printed Arabic letter based on boundary characteristic in Sep. 19, 2007. This method takes four boundaries of upside, downside, left and right of letters as a wave and expresses each boundary as an aggregation of a series of wave elements; then the boundary characteristics such as the number of the wave elements, the number of zero-line, the length of a first zero-line on the right boundary, the length of a first zero-line on the downside boundary, the length of a longest zero-line on the upside boundary, the length of a longest zero-line on the right boundary, the length of a longest zero-line on the downside boundary, and the number of positive-line on the upside boundary are extracted from the aggregations, and theses boundary characteristics combined with the depth-width ratio of letter and the depth-width ratio of an accessorial part of letter serve as identifying characteristic; at last, each printed Arabic letter is identified by four decision trees based on the four formats of letter: independence, beginning, middle and end respectively. This identifying method expresses the letter boundary as an aggregation of various wave elements, and extracts the characteristic of various wave elements from the aggregation. The extracting process is simple, fast and convenient. However, this identifying method is only effective to the printed Arabic letter, and is unstable to extract the characteristic of the hand-written Arabic letter. At the same time, the decision tree is not very adaptive to the deformation of the letter shape, which is a disadvantage to identify the hand-written Arabic letter. Furthermore, the deformation of the hand-written Arabic letter is very complex, so that the researches mainly concentrate on the identification of printed Arabic letter instead of the identification of hand-written Arabic letter.